ǂThe ǂcontemporary approach to CALR-positive myeloproliferative neoplasms

Tanja Belčič Mikič (Author), Tadej Pajič (Author), Samo Zver (Author), Matjaž Sever (Author)

Abstract

CALR mutations are a revolutionary discovery and represent an important hallmark of myeloproliferative neoplasms (MPN), especially essential thrombocythemia and primary myelofibrosis. To date, several CALR mutations were identified, with only frameshift mutations linked to the diseased phenotype. It is of diagnostic and prognostic importance to properly define the type of CALR mutation and subclassify it according to its structural similarities to the classical mutations, a 52-bp deletion (type 1 mutation) and a 5-bp insertion (type 2 mutation), using a statistical approximation algorithm (AGADIR). Today, the knowledge on the pathogenesis of CALR-positive MPN is expanding and several cellular mechanisms have been recognized that finally cause a clonal hematopoietic expansion. In this review, we discuss the current basis of the cellular effects of CALR mutants and the understanding of its implementation in the current diagnostic laboratorial and medical practice. Different methods of CALR detection are explained and a diagnostic algorithm is shown that aids in the approach to CALR-positive MPN. Finally, contemporary methods joining artificial intelligence in accordance with molecular-genetic biomarkers in the approach to MPN are presented.

Keywords

kalcij;mieloproliferativne neoplazme;diagnostika;trombocitemija;umetna inteeligenca;calreticulin;chaperone;calcium;myeloproliferative neoplasm;diagnostics;thrombocythemia;artificial intelligence;

Data

Language:	English
Year of publishing:	2021
Typology:	1.02 - Review Article
Organization:	UL MF - Faculty of Medicine
UDC:	616.1
COBISS:	57640451
ISSN:	1422-0067
Views:	123
Downloads:	40
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	kalcij;mieloproliferativne neoplazme;diagnostika;trombocitemija;umetna inteligenca;
Type (COBISS):	Article
Pages:	str. 1-16
Volume:	ǂVol. ǂ22
Issue:	ǂiss. ǂ7
Chronology:	2021
DOI:	10.3390/ijms22073371
ID:	14657165